Methods of data acquisition and data processing in a vehicle are conventional. Data acquisition methods may be used, for example, to prepare warnings for the driver of a vehicle. With such systems, variables derived from several original variables can also be generated. However, there may be known methods in which the data is recorded as a function of time and location and this information is taken into account in processing the data. However, it has become increasingly important to acquire the greatest possible number of relevant variables, i.e., those appearing to be relevant, and the changes in such variables in order to thereby be able to compile more extensive statistics regarding individual driving performance as a function of environmental and vehicular states and/or changes therein. However, recording all variables for possible subsequent analysis may result in enormous volumes of data, even in the case of rough time discretization, thus compromising both the efficacy of storage as well as the efficacy of the subsequent analysis.